Why "Intelligent Design" is more interesting than old-fashioned
creationism

By Taner Edis

Posted October 6, 2005

When the Intelligent Design (ID) movement attracts the attention of
mainstream scientists, it does so as the latest incarnation of
creationism. The ID literature reinforces this impression. ID
proponents devote most of their efforts to denouncing "Darwinism," by which they
mean naturalistic theories of evolution. Some ID proponents accept common
descent, some do not. But the ID movement is united in thinking that
mindless mechanisms 末 Darwinian variation-and-selection in particular 末 cannot
account for the diversity and complexity of life.

If ID was only a collection of neocreationist claims concerning biology, it
would be relatively straightforward to address. For example, the most
prominent biology-related argument for ID has been due to biochemist Michael
Behe [1], who claimed that certain molecular machines were "irreducibly
complex." Structures such as the bacterial flagellum, he argued, could not
be assembled gradually through a series of functional intermediate forms -- all of
their many components had to come together at once. Critics immediately
pointed out that systems and their components need not have had the same
functions throughout their history. Indeed, Behe has lately shifted his
emphasis away from his original argument.

Instead, Behe and other ID proponents' current arguments for design in
biology describe the interlocking complexity of biochemical systems and state
that it is implausible that they could have been assembled gradually. They then
say that "Darwinists" have to supply a fully-articulated sequence of successive
changes; otherwise Darwinian evolution can be dismissed as mere speculation
[2]. Such attempts at shifting the burden of proof do not impress many
scientists. Though incomplete, evidence that, for example, eubacterial
flagella are related to and have evolved as secretory mechanisms [3] is
compelling. Biologists need to update their responses to creationism,
addressing old arguments that have now been cast in a biochemical idiom, but
otherwise ID presents no challenge to biology.

Then there is ID and physical science. Unlike the biblically literalist
champions of Young Earth Creationism, ID proponents tend to accept an old
universe or take no position on the matter of age. Nevertheless, ID
includes physical claims as well. Their main concern is identifying
supposed mysteries such as fine-tuning in astronomy and physical cosmology and
proclaiming these as evidence of design [4]. Though fine-tuning arguments have
found favor among some theological liberals as well as in ID, they appear to be
useless in terms of advancing science [5]. So again, if all ID did was to
retool old-fashioned intuitions about divine design, the scientific response to
ID would not need to extend beyond adapting standard responses to
creationism. There would be little of intellectual interest in criticizing
ID.

However, though the bulk of ID literature is devoted to recycling old errors,
there are some aspects of ID that are more interesting mistakes 末 where
figuring out exactly how ID goes wrong can help us advance our knowledge and
understand evolution better. One area where ID gets interesting is in its
claims about intelligence.

ID proponents have vigorously engaged in philosophical debates about whether
naturalistic explanations are required in science. They find
methodological naturalism to be an unjustified constraint on our ways of
investigating the world. They would like, ultimately, to introduce
intelligent agents as a fundamental cause in scientific
explanations. This seems reasonable enough; after all, sciences such as
archaeology explain many of their findings by human agency. However, ID
claims much more than an ability to identify the work of agents about which
plenty is known independently [6]. Human and animal intelligence can
plausibly seen to be part of the natural world. ID is fundamentally
revolutionary point of view only if intelligent agency is somehow beyond natural
mechanisms.

To flesh out such ideas, ID thinkers observe that today's natural scientific
explanations only make use of randomness and of lawful, patterned events 末 in
biologist Jacques Monod's terms, "chance and necessity" [7]. A physicist
may predict a planetary orbit by writing down the appropriate equations from a
theory of gravity, or describe radioactive decays as being completely
random. In general, the physical world behaves according to combinations
of chance and necessity. Biology follows the pattern of modern physics
when explaining evolutionary adaptation. The raw novelty in the genome comes
from blind variation and mutation 末 largely due to chance. This variation is then
subjected to nonrandom selection. In other words, biology also combines chance
and necessity in its central theories. Furthermore, this approach has been so
successful in modern science that it motivates a more comprehensive physicalism,
according to which everything in our world is physically realized [8]. ID
claims that this is incorrect 末 that intelligent design is a third, independent
mode of explanation that is not reducible to chance and necessity.
Intelligence, in the ID view, is beyond physics.

A number of the leading lights of ID have presented the claim that meaningful
information can only be created by intelligence, and that intelligence is
beyond chance and necessity, as a central aspect of ID [9]. In particular,
William A. Dembski, the leading theoretician of ID, has explicitly argued that
ID is a third option [10]. Moreover, he has proposed what he claims is a
mathematically rigorous way to tell if a certain data set contains "complex
specified information" (CSI) which is supposed to be the signature of an
intelligent cause. In fact, CSI, in Dembski's view, is just a
pre-specified pattern which is extremely improbable to be produced by any
combination of chance and necessity. At the heart of Dembski's version of
ID [11,12] are two propositions:

There is a rigorous mathematical procedure to detect CSI, which is a
reliable signature of intelligent design.

Intelligent agency is not reducible to any combination of chance and
necessity.

If these two claims could be sustained, ID proponents would be justified in
their hopes to usher in a scientific revolution. In fact, they could claim
some success even if their efforts to cast doubt on biological evolution should
continue to fizzle out. This is because ID, especially in Dembski's
version, is primarily a claim about complexity and about intelligence 末 not just
biology. Even if biologists are (as they almost certainly are) correct
about common descent, and if they are right about some of the mechanisms behind
evolution, all would not be lost for ID. If propositions 1 and 2 are
correct ID proponents could still infer a guiding intelligence behind biological
complexity 末 the designer would then have injected all the necessary CSIinto the world in the beginning. Regardless of any philosophical
wrangling about methodological naturalism, ID proponents can also state that
this designing intelligence is something beyond mere physical mechanisms.

None of this is likely to happen. Just in the past few decades, natural
scientists have continued to learn a lot not just about the details of
biological evolution, but also the physics of complexity and the nature of human
and possibly even machine intelligence. None of this new knowledge is any
comfort to ID. It is still possible to find a few thinkers with ID
sympathies who think that concepts of self-organization in nonequilibrium
thermodynamics pose a challenge to mainstream biology [13]. However, these
are intellectually marginal currents. In the study of complexity, the
overwhelming trend is toward an invigorating synthesis of perspectives from
biology, physics, computer science and other relevant disciplines.
So it is very implausible that ID should be correct. Most scientists who
pay any attention to ID therefore ignore the substantive claims involved in ID
and concentrate on countering its political influence.

Nevertheless, a number of scientists and science-oriented philosophers have
examined the claims of ID in detail. In particular, Dembski's work
summarized in proposition 1 above has come in for heavy criticism. Dembski
hopes to detect design through examining a data set and eliminating chance and
necessity as possible explanations. We infer design regularly in everyday
life, and it is certainly interesting to try and formalize the reasoning we use
to do so. Dembski proposes a rigorous way of making design inferences, and
his initial effort was intriguing enough to be published by a reputable academic
press [14]. However, though it may have some intuitive appeal, it has
become clear that Demsbki's procedure suffers from numerous fatal problems
[15]. For example, he often assumes a uniform probability distribution to
calculate a very small probability for a structure, and then takes this as
reason to eliminate all element of "chance" as part of its
explanation. Even his notion of CSI appears to be ill-conceived and badly
defined, and it certainly has little to do with "information" as understood in
mainstream work in information theory [16]. Indeed, some critics have
judged that Dembski's work is of very low quality and has little substance to be
taken seriously [17]. Dembski later tried to bolster his position by
making use of the "no free lunch" theorems, arguing that blind mechanisms cannot
create CSI but smuggle the information in from carefully chosen fitness
landscapes [18]. Again, numerous basic errors plague this argument as well
[19]. In short, Dembski and the ID movement as a whole have achieved
nothing close to a rigorous way to detect design; they only have some intuitions
that at the most have some vague commonsense appeal.

If modern science shows us anything, it is that our intuitions can fail
spectacularly outside the domain of everyday life. Still, intuitions do
not get discarded lightly. Even with its numerous technical errors, ID
proponents might remain confident that there is something to Dembski's
approach. After all, they often say, ID is a new paradigm. We cannot
expect it to appear on the scene fully worked out, entirely free of
problems. Dembski or others may have to go back to the drawing
board, but the basic intuition that intelligence is something beyond
natural processes will remain ever-ready to be resurrected.

So some critics of ID also ask if there is some deeper flaw in the intuitions
driving ID, something not even a retooled, patched up design-detection procedure
akin to Dembski's can overcome. For example, philosopher of biology
Elliott Sober points out that design arguments (including ID) are problematic
because they can succeed only given independent knowledge about the goals and
abilities of the designer [20]. If so, Dembski-style attempts to infer
that some data is a result of design without making assumptions about the nature
of the designer are inherently flawed.

Sober's critique assumes that the likelihood form of design arguments are
most defensible. But Dembski takes a different approach. If
Dembski's CSI (or whatever new and improved variation ID can come up with)
cannot indeed be assembled by chance and necessity, such criticisms would be
moot. Moreover, Dembski's attempts to formalize a design inference
implicitly includes knowledge about the kind of things human intelligence
produces. ID proponents overwhelmingly come from conservative theistic
backgrounds, and it is no secret that their designer is a personal, at least
somewhat anthropomorphic God. So whatever the difficulties of generic
design arguments in philosophy, it is not true that ID includes no expectations
about designers 末 though the ID movement does not care to emphasize this,
possibly for legal reasons.

To undercut the intuitions behind ID, we need something more: to explicitly
argue that intelligence itself is a product of chance and necessity.
Imagine that we were presented with a complex mathematical procedure useful in
detecting design 末 that something related to proposition 1 were correct.
This procedure could be a useful scientific tool; to borrow an example from
Dembski, its uses might include tasks such as SETI astronomers figuring out if a
signal they detected was produced by an alien intelligence (though SETI
researchers today approach their problem quite differently than Dembski).
But if we had good reasons to think proposition 2 were mistaken, then ID would
still have no purchase on reality.

We have such reasons. The details of the argument, which rely on some
of the technical apparatus of theoretical computer science, have been presented
elsewhere [21,22]. In outline, however, it can be summarized.

Let us first characterize Dembski's approach to detecting design.
Dembski might observe that if we encounter a slip of paper with "Bu sabah hava
çok güzel, ama belki sonra bozabilir, belli degil..." printed on it, we have a
very good notion that it is a meaningful message, even if we do not know Turkish
and so have no clue what it means. We know enough about natural languages
to see that it fits the appropriate pattern. Moreover, we can distinguish
it from simple rule-generated strings such as "qaqaqaqaqaqaqaqa..." (the rule
being "repeat 'qa' over and over") and random gibberish such as "uwl wdfjw2f
af2h7kcfje/jvbppwvjo...". The Turkish sentence looks like the sort of thing
an intelligence would produce. There is some nonrandom content in it, even
if we do not know what it signifies. It might have been printed out by a
computer, but in that case, we know that the actual content must have been
pre-programmed into the machine. Machines are devices that work according
to chance and necessity. And so Dembski argues that machines cannot create
new CSI 末 they can only preserve or degrade the meaningful content.

Now, Dembski wants to infer design only from the message itself, without any
knowledge of how it was produced. In that case, there is the question of
distinguishing between a message printed by a computer and one scribbled out by
a human. How can we say that the human is a genuinely intelligent source
of new information, while a machine cannot do any such thing?

This is a long-standing question confronting researchers in artificial
intelligence (AI), and it is no surprise that many ID proponents, including
Dembski, have endorsed the position that humans can do things no mere machine is
able to. In arguing against evolution, ID proponents continually assert
that chance and necessity cannot assemble meaninful genetic information.
Against AI, ID takes the same line: assert that chance and necessity cannot
produce genuine novelty 末 that it cannot produce complex information. We
know that humans are the source of new information, because we are flexible,
creative, not bound by pre-set rules. Computers, by contrast, only follow
pre-programmed rules.

The flaw in such an argument is that it does not adequately consider
combinations of chance and necessity 末 in the computer context, procedures
combining algorithms and randomness. As it happens, we know a good deal
about just what a machine with access to a truly random function can accomplish
and what it cannot. It turns out that the only tasks not performable by
combinations of chance and necessity are certain "oracles," and we know of
nothing (humans included) that realizes such oracle-functions. In
particular, information-containing output and creative tasks that introduce
genuine novelty are not beyond machines that combine rules and randomness
[22]. "Artificial life" research provides some particularly telling
examples [23]. Demsbki's CSI is not and cannot be a signature for a
kind of result no machine can ever produce. In a way reminiscent of
Darwinian evolution (not coincidentally) randomness serves as a source of raw
novelty, not conditioned by any rules. Rules, including interactions with
a machine's environment and with other machines, shape the raw novelty into
something that is meaningful in its local context.

AI research faces a problem similar to what biologists once did: how to
create meaningful information. And the Darwinian mechanism of
variation-and-selection is a beautiful solution to precisely this problem.
Hence much recent work in AI has taken a Darwinian turn. Moreover, recent
thinking in the cognitive and brain sciences also highlights the role of
Darwinian mechanisms in our own brains. So we can say, with considerable
confidence, that intelligence is nothing supernatural. Intelligence is
achieved by mechanisms combining chance and necessity, within the realm of
ordinary physics.

ID falls hopelessly afoul of today's understanding of complexity and
information. This understanding, still partial and ever-expanding,
combines insights from many separate disciplines. Physics sets the stage
by describing a world operating according to chance and necessity.
Physicists also help us understand how complex systems work by exploring
self-organization and nonequilibrium thermodynamics, giving us clues about how
complex self-replicating systems form. The mathematics underlying computer
science gives us rigorous definitions of complexity and information, and a
common language in a day when much of theoretical science has come to depend
heavily on computer simulations. Cognitive and brain sciences, even though
they remain far from maturity, still tell us much about human intelligence that
illuminates how chance and necessity combine to achieve complexity. But
the centerpiece of our modern understanding of complexity comes from biology:
Darwinian variation and selection. Darwin's mechanism is the answer to the
question of how chance and necessity can bring genuinely new information into
the world.

ID proponents are right to highlight the question of the origin of
information. This is an interesting question. However, they
treat information as a mysterious quantity and fail to make connections to
established research concerning information. On top of this, they do not
realize or do not acknowledge that mainstream science already possesses the
critical elements of a satisfying answer to their question. In their
political opposition to evolutionary science, ID proponents promise to be a
significant irritant for scientific and educational institutions [24]. But
in responding to ID, its critics also have an opportunity to highlight today's
developing multifaceted, interdisciplinary understanding of evolution and
complexity. If more scientists thereby become more aware of how their
specialties fit together with natural science as a whole, then ID might
indirectly be of service to science after all.

Acknowledgments

The Education Committee of the Association of Southeastern Biologists provided funding for and expedited the symposium at which the talk which led to this paper was presented. The paper originally appeared in Georgia Journal of Science 63:3 189 (2005).

[3] Musgrave I: Evolution of the bacterial flagellum. In Why Intelligent
Design Fails: A Scientific Critique of the New Creationism (Young and Edis,
Eds) New Brunswick, NJ: Rutgers University Press, 2004.

[4] Gonzalez G and Richards JW: "The Privileged Planet: How Our Place in the
Cosmos is Designed for Discovery." Washington, DC : Regnery Publishing, 2004.

[5] Jefferys WH: Review of The Privileged Planet. Reports of the
National Center for Science Education, forthcoming.

[6] Hurd GS: The explanatory filter, archaeology, and forensics. In Young and
Edis 2004.

[7] Monod J: "Chance and Necessity: An Essay on the Natural Philosophy of
Modern Biology." New York: Vintage Books, 1972.

[23] Sims K: Evolving 3D Morphology and Behavior by Competition. In
Artificial Life IV: Proceedings of the Fourth International Workshop on the
Synthesis and Simulation of Living Systems (Brooks and Maes, Eds) Cambridge:
MIT Press, 1994.